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Workshop
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Learning to Continually Learn with Topological Regularization
Tananun Songdechakraiwut · Xiaoshuang Yin · Barry Van Veen
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Workshop
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Scalable Vector Representation for Topological Data Analysis Based Classification
Tananun Songdechakraiwut · Bryan Krause · Matthew Banks · Kirill Nourski · Barry Van Veen
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Workshop
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Group invariant machine learning by fundamental domain projections
Benjamin Aslan · Daniel Platt · David Sheard
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Workshop
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A Generalized Framework for Microstructural Optimization using Neural Networks
Saketh Sridhara · Aaditya Chandrasekhar · Krishnan Suresh
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Workshop
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Spectrum Guided Topology Augmentation for Graph Contrastive Learning
Lu Lin · Jinghui Chen · Hongning Wang
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Workshop
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Topological Classification in a Wasserstein Distance Based Vector Space
Tananun Songdechakraiwut · Bryan Krause · Matthew Banks · Kirill Nourski · Barry Van Veen
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Workshop
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Topological Jet Tagging
Dawson Thomas · Sarah Demers · Smita Krishnaswamy · Bastian Rieck
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Workshop
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Topological Continual Learning with Wasserstein Distance and Barycenter
Tananun Songdechakraiwut · Xiaoshuang Yin · Barry Van Veen
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Affinity Workshop
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Comparing neural population responses based on pairwise p-Wasserstein distance between topological signatures
Liu Zhang · Fei Han · KELIN XIA
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Workshop
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Fuzzy c-Means Clustering in Persistence Diagram Space for Deep Learning Model Selection
Thomas Davies · Jack Aspinall · Bryan Wilder · Long Tran-Thanh
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Workshop
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An Adversarial Robustness Perspective on the Topology of Neural Networks
Morgane Goibert · Elvis Dohmatob · Thomas Ricatte
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Workshop
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Sat 9:10
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Do Neural Networks Trained with Topological Features Learn Different Internal Representations?
Sarah McGuire · Shane Jackson · Tegan Emerson · Henry Kvinge
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